Download Cytoscape 2.1

Cytoscape
2.1
User Manual
Feb. 2005
The Cytoscape Collaboration
The Cytoscape project is an ongoing collaboration between:
University of California at San Diego
Memorial Sloan-Kettering Cancer Center
Institute for Systems Biology
Institut Pasteur
Funding for Cytoscape is provided by a federal grant from the U.S. National Institute of General Medical
Sciences (NIGMS) of the National Institutes of Health (NIH) under award number GM070743-01.
Corporate funding is provided through a contract from Unilever PLC.
Table of Contents
1. INTRODUCTION.................................................................................................................................................. 3
2. LAUNCHING CYTOSCAPE ................................................................................................................................ 3
3. QUICK TOUR OF CYTOSCAPE......................................................................................................................... 5
4. COMMAND LINE ARGUMENTS AND PROPERTIES ................................................................................. 10
5. BUILDING AND STORING INTERACTION NETWORKS.......................................................................... 13
6. LOADING GENE EXPRESSION DATA........................................................................................................... 17
7. NODE AND EDGE ATTRIBUTES..................................................................................................................... 20
8. NAVIGATION AND LAYOUT........................................................................................................................... 22
9. VISUAL STYLES ................................................................................................................................................ 24
9.1
9.2
9.3
9.4
9.5
INTRODUCTION TO VISUAL STYLES .................................................................................................................. 24
VISUAL ATTRIBUTES, GRAPH ATTRIBUTES AND VISUAL MAPPERS .................................................................. 27
TUTORIAL: CREATING A NEW VISUAL STYLE .................................................................................................. 30
TUTORIAL: CREATING A NEW VISUAL STYLE WITH A DISCRETE MAPPER ....................................................... 32
TUTORIAL: VISUALIZING EXPRESSION DATA ON A NETWORK ......................................................................... 33
10. FILTERS.............................................................................................................................................................. 34
11. ACKNOWLEDGEMENTS................................................................................................................................ 39
APPENDIX: ANNOTATION SERVER FORMAT............................................................................................... 40
INTRODUCTION........................................................................................................................................................ 40
BUILDING YOUR OWN ANNOTATION FILES ............................................................................................................... 40
LOAD DATA IN-PROCESS ........................................................................................................................................ 42
GETTING AND REFORMATTING GO DATA ............................................................................................................... 43
APPENDIX: GNU LESSER GENERAL PUBLIC LICENSE.............................................................................. 48
1. Introduction
Cytoscape is an open-source community software project for integrating biomolecular interaction
networks with high-throughput expression data and other molecular states into a unified
conceptual framework. Although applicable to any system of molecular components and
interactions, Cytoscape is most powerful when used in conjunction with large databases of
protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans
and model organisms. A software “Core” provides basic functionality to layout and query the
network; to visually integrate the network with expression profiles, phenotypes, and other
molecular states; and to link the network to databases of functional annotations. The Core is
extensible through a straightforward plug-in architecture, allowing rapid development of
additional computational analyses and features. The central organizing metaphor of
Cytoscape is a network graph, with genes, proteins, and molecules represented as nodes
and interactions represented as links, i.e. edges, between nodes.
Development
Cytoscape is a collaborative project between the Institute for Systems Biology (Dr. Hamid
Bolouri), the University of California San Diego (Dr. Trey Ideker), Memorial Sloan-Kettering
Cancer Center (Dr. Chris Sander) and the Institut Pasteur (Dr. Benno Schwikowski).
Visit http://www.cytoscape.org for more information.
License
Cytoscape is protected under the GNU LGPL (Lesser General Public License). The License is
included as an appendix to this manual, but can also be found online:
http://www.gnu.org/copyleft/lesser.txt Cytoscape also includes a number of other open source
libraries, which are detailed in Section 10, Acknowledgements below.
2. Launching Cytoscape
Currently, Cytoscape runs under Java on Linux, Windows, and Mac OS X. Although Cytoscape
handles arbitrary types and sizes of interaction network, it is most powerful when used in
conjunction with large interaction data sets such as are currently available for species such as
Saccharomyces cerevisiae (budding yeast).
System requirements:
The system requirements for Cytoscape depend on the size of the networks the user wants to
load, view and manipulate. We recommend a recent computer (1GHz CPU or higher) with a
high-end graphics card and at least 256MB of free physical RAM. Cytoscape expects a minimum
screen resolution of 1024x768.
(1) Download and unpack the distribution. Cytoscape is distributed as a compressed archive
(tar.gz or zip) containing the following files and directories:
cytoscape.jar
cytoscape.props
vizmap.props
Main Cytoscape application (Java archive)
User-configurable properties and preferences
User-configurable visual mapping preferences
cytoscape.sh
cytoscape.bat
Script to run Cytoscape from command line (Linux, Mac OS X)
Script to run Cytoscape (Windows)
LICENSE.txt
Cytoscape2_1Manual.pdf
Cytoscape GNU License
Cytoscape 2.1 Manual (the document you are reading now)
sampleData/
galFiltered.gml
galFiltered.sif
galExpData.pvals
BINDyeast.sif
BINDhuman.sif
yeastHighQuality.sif
Sample molecular interaction network file *
Identical network in Simple Interaction Format *
Sample gene expression matrix file *
Network of all yeast protein-protein interactions in the BIND
database as of July, 2004 **
Network of all human protein-protein interactions in the BIND
database as of July, 2004 **
Sample molecular interaction network file ***
annotation/
Directory containing Gene Ontology database entries (currently for
yeast only). Info in this directory is used to associate gene names
with synonyms as well as process, function, and cellular location
data.
plugins/
Directory containing cytoscape PlugIns, in .jar format.
* From Ideker et al, Science 292:929 (2001)
** Obtained from data hosted at http://www.blueprint.org/bind/bind_downloads.html
** From von Mering et al, Nature, 417:399 (2002) and Lee et al, Science 298:799 (2002)
(2) If necessary, install Java. If not already installed on your computer, download and install
the Java 2 Runtime Environment, version 1.4.2 or higher. It can be found at:
http://java.sun.com/j2se/1.4.2/download.html
(3) Launch the application by running "cytoscape.sh" from the command line (Linux or Mac
OS X) or double-clicking "cytoscape.bat" (Windows). Alternatively, you can pass the .jar file to
Java directly using the command "java -jar cytoscape.jar". In Windows, it is also possible to
directly double-click the .jar file to launch it. However, this does not allow specification of
command-line arguments (such as the location of the annotation data directory, see the section 4.
Command Line Arguments for details). On Mac OS X, users who downloaded the Mac OS X
version of Cytoscape, can double-click on the Cytoscape icon to start Cytoscape. Either double-
clicking or dragging onto the Cytoscape application any .sif or .gml file will load that file into
Cytoscape.
! Important Note:
For the application to work properly, ALL FILES MUST BE LEFT IN THE
DIRECTORY IN WHICH THEY ARE UNPACKED. The core Cytoscape
application assumes this directory structure when looking for certain files, such
as cytoscape.props, vizmap.props, and the annotation/ database.
Cytoscape Window
When you succeed in launching Cytoscape, a window will appear that looks like this:
3. Quick Tour of Cytoscape
When a network is loaded, Cytoscape will look something like the image on the next page:
The main window has five components:
1. The menu bar at the top (See below for more information about each menu item).
2. The toolbar, which contains icons for commonly used functions. These functions are also
available via the menus. Hover the mouse pointer over an icon and wait momentarily for
a description to appear as a tooltip.
3. The network management window (top-left white box).
4. The overview window (bottom-left overview of the network).
5. The main network view window, which displays the network.
The Menus
File
The File menu contains most basic file functionality: File / Load for loading a
variety of file types; File / Save for saving. File/Help displays a credits screen.
File / Print allows printing. File / Export As... allows you to export to a file in a
number of graphics formats (such as postscript). File / Exit closes all windows
of Cytoscape and exits the program.
Edit
The Edit menu contains a Squiggle feature that enables you to mark up
your network. This can be particularly useful during live presentations.
There are also options for creating and destroying views (graphical
representations of a network) and networks (the network data – not yet
visualized).
The Edit Menu also supports Preferences editing for properties and
plug-ins via a Preferences Dialog. Preferences editing operates on the cytoscape.props file
associated with the user’s instance of Cytoscape. See “Commands Line Arguments and
Properties” for more information.
Data
The Data menu allows you to display the attribute browser, which
lets you view attributes assigned to both nodes and edges. (See
the section 7. Node and Edge Attributes) Other options shown
relate to plugins which are packaged with Cytoscape 2.1.
Select
The Select menu contains methods and operations for selecting
nodes and edges, and using the current selection to create a new
network and an associated view.
Layout
The Layout menu has an array of features for organizing the network
visually according to one of several algorithms, aligning and rotating
groups of nodes, and adjusting the size of the network. Most of these
features are available from plugins that are packaged with Cytoscape
2.1
Visualization
The Visualization menu provides options for changing the mapping
from biological data to a visual representation: colors of nodes,
thickness of edges, etc. These features are explored in-depth in the 9.
Visual Styles section. This menu also provides an Overview (Bird’s
Eye view) of your entire network, which is helpful for navigating very
large networks.
PlugIns
The PlugIns menu has menu entries or choices added by plugins that
have been loaded, such as "Find Enriched Attributes".
Note: A list of Cytoscape PlugIns with descriptions is available online at:
http://cytoscape.org/plugins2.php
Filters
This menu has been added by the plugin in the file "filter.jar". The function of this plugin is not
described further in this manual. Additional menus may appear, depending on the set of PlugIns
you have chosen to load.
Help
The Help menu allows users to launch the online help viewer and browse
the table of contents (Contents…), or view the help text associated with a
context-sensitive selection (Context Sensitive…). By selecting Context
Sensitive… menu item and then selecting a GUI component, the help
related to the selected item is launched. The “About…” menu item displays information about
the running version of Cytoscape.
The Network Management Window
Cytoscape 2.1 allows multiple networks to be loaded at a time, either with or without a view. A
network stores all the nodes and edges that are loaded by the user and a view displays them. You
can have many views of the same network. Networks (and their optionally associated views) can
be organized hierarchically.
An example where a number of networks have been loaded and arranged hierarchically is shown
below:
The network manager (marked by the red square) shows the networks that are loaded. Clicking
on a network here will make that view active in the main window, if the view exists (green
highlighted networks only). Each network has a name and size (number of nodes and edges),
which are shown in the network manager. If a network is loaded from a file, the network name
is the name of the file.
Since some networks are very large (thousands of nodes and edges) and can take a long time to
display. For this reason, a network in Cytoscape may not contain a ‘view’. Networks that have a
view are highlighted in green and networks that don’t have a view are highlighted in red. You
can create or destroy a view for a network by right-clicking the network name in the network
manager or by choosing the appropriate option in the edit menu. You can also destroy previously
loaded networks this way. In the picture above, five networks are loaded, three green ones with
views and two red ones without views.
Certain operations in Cytoscape will create new networks. If a new network is created from an
old network, for example by selecting a set of nodes in one network and copying these nodes to a
new network (via the Select->To New Network option), it will be shown as a child of the
network that it was derived from. In this way, the relationships between networks that are loaded
in Cytoscape can be seen at a glance.
The available network views are also shown as tabs on the top of the view window. You can
click on the tab to go to the named network and the network manager will update accordingly.
Advanced users: Cytoscape also has two viewing modes that alter the way in which these
windows are displayed. This mode can only be selected on startup of the program by adding the
–t option on the command line (see section 4. Command Line Arguments).
The Network Overview Window
The network overview window shows an overview (or ‘bird’s eye view’) of the network. It can
be used to navigate around a large network view. This feature can be turned on an off via the
Visualization menu. The red-outlined blue rectangle in the overview window shown below can
be dragged with the mouse to navigate to a part of the network. The size of the navigation
rectangle depends on the size of the active view and the zoom level of the view. The rectangle is
smaller if the view is zoomed in and larger if zoomed out.
4. Command Line Arguments and Properties
Cytoscape recognizes a number of optional command line arguments, including run-time
specification of network files and expression data:
-g | -graph <GML network filename> (xxx.gml)
Loads a network file in GML format (see 5. Building and
Storing Interaction Networks)
-i | -interaction <SIF interactions filename>
(yyy.sif)
Loads a network file in SIF format (see 5. Building and
Storing Interaction Networks)
-b | -BDS <bioData directory>
(e.g. annotation/manifest)
Specifies which directory to use for the BioDataServer
annotations
-e | -expression <expression filename> (zzz.pvals)
Loads an expression data file (see 6. Loading Gene
Expression Data)
-n | -nodeAttributes <nodeAttributes filename> (one or more)
Loads node attributes files (see 7. Node and Edge
Attributes)
-j | -edgeAttributes <edgeAttributes filename> (one or more)
Loads edge attributes files
(see 7. Node and Edge Attributes)
-s | -species
Set the default species name
-c | -noCanonicalization
Turn off default node name canonicalization
-h | -help | -help | --help
Help: display these command line arguments
-p | -plugin | --JLD | --JLW | --JLL Specify a list of plugins (jar files), directories containing
plugins, URLs (http://) to jar files, or URLs to manifest
files listing jar files
-props <properties file>
specify and load a properties file
-headless | -noView
Run in headless mode; do not create and display the GUI
-noDialog | -suppressView
Do not popup informational dialog when express file is
loaded
Specify the threshold # of nodes at which views will not
automatically be created
-vt | --VT <view threshold>
-project <project file>
Specify the location of the project file
-script | --script <script text…> -endSpecify script text
-rp | -resourcePlugin <resource plugins…>
Specify the list of resource plugins
Note that most data sets may also be loaded after Cytoscape is running. See sections 5. Building
and Storing Interaction Networks, 6. Loading Gene Expression Data, and 7. Node and Edge
Attributes for details.
Additional command line arguments that are not recognized by the Cytoscape core are passed to
the PlugIn modules. Please refer to the documentation for each specific PlugIn for more details.
Cytoscape Properties
The Cytoscape Preferences Dialog, accessed via Edit->Preferences…, has sections for general
properties display/editing and plugins specification via the properties mechanism. Preferences in
Cytoscape are stored in the form of Java properties
specified in the cytoscape.props file located in the
users’ working directory, home directory or
Cytoscape distribution directory. This file is
automatically loaded at startup time and written
upon normal exit of the application.
Cytoscape properties are displayed in the Properties
section of the dialog. These properties are
configurable via Add, Modify and Delete
operations.
The specification of plugins to be loaded into
Cytoscape at startup time is also supported in
cytoscape.props and accessible in this dialog under
the Plugins section. In this special case, the plugins
property specifies a comma-separated list of jar
files or URLs to jar files containing plugins. This
property is parsed into its constituents and
presented and managed in the Plugins table, as at left.
Some common properties are described below.
Property name
Default
value
defaultSpeciesName
PleaseSpecify species names
this value must match the name in the
first line of the file specified in the
bioDataServer’s manifest for synonyms
e.g., for yeast synonyms, specify
Saccharomyces cerevisiae
PleaseSpecify annotation/manifest, and other manifest
file locations
500
integers > 0
bioDataServer
viewThreshold
secondaryViewThreshold 2000
Valid values
integers > 0
Related
command
line
argument
-s
-species
-b
-BDS
-vt
--VT
Property name
Default
value
Valid values
viewType
plugins
tabbed
tabbed
comma-separated list of jar files
containing plugins, or URL’s to jar files
containing plugins (e.g.,
http://server/my-plugin.jar)
Related
command
line
argument
-p
-plugin
--JLD
--JLW
--JLL
Java System properties
Cytoscape also honors a new Java system property introduced in Java 1.4: java.awt.headless.
This property allows the Java system to run without Graphics support; Cytoscape running in this
mode allows users to run non-graphical analyses as batch jobs or on systems without
keyboard/mouse/display capabilities, such as compute servers.
-Djava.awt.headless=[ true | false ] Similar to command line argument –headless | -noView;
run in headless mode, do not create and display the GUI
5. Building and Storing Interaction Networks
Cytoscape reads an interaction network in two ways: from a simple interaction file (SIF or .sif
format) or from a standard format known as Graph Markup Language (GML or .gml format).
SIF specifies nodes and interactions only, while GML stores additional information about
network layout and allows network data exchange with a variety of other network display
programs. Typically, SIF is used to import interactions when building a network for the first
time, since it is easy to create in a text editor or spreadsheet. Once the interactions have been
loaded and layout has been performed, the network may be saved to and subsequently reloaded
from GML format in future Cytoscape sessions. Both SIF and GML are ASCII text files, and
you can edit and view them in a regular text editor. Additionally, GML is supported by some
other network visualization tools.
SIF FORMAT:
The simple interactions format is convenient for building a graph from a list of interactions. It
also makes it easy to combine different interaction sets into a larger network, or add new
interactions to an existing data set. The main disadvantage is that this format does not include
any layout information, forcing Cytoscape to re-compute a new layout of the network each time
it is loaded.
Lines in the SIF file specify a source node, a relationship type (or edge type), and one or more
target nodes:
nodeA
nodeC
nodeD
nodeG
...
nodeY
<relationship type> nodeB
<relationship type> nodeA
<relationship type> nodeE nodeF nodeB
<relationship type> nodeZ
A more specific example is:
node1 typeA node2
node2 typeB node3 node4 node5
node0
The first line identifies two nodes, called node1 and node2, and a single relationship between
node1 and node2 of type typeA. The second line specifies three new nodes, node3, node4, and
node5; here "node2" refers to the same node as in the first line. The second line also specifies
three relationships, all of type typeB and with node2 as the source, with node3, node4, and
node5 as the targets, respectively. This second form is simply shorthand for specifying multiple
relationships of the same type with the same source node. The third line indicates how to specify
a node that has no relationships with other nodes. This form is not needed for nodes that do have
relationships, since the specification of the relationship implicitly identifies the nodes as well.
Duplicate entries are allowed and indicate multiple edges between the same nodes. For example,
the following specifies three edges between the same pair of nodes, two of type pp and one of
type pd:
node1 pp node2
node1 pp node2
node1 pd node2
Edges connecting a node to itself (self-edges) are also allowed:
node1 pp node1
Every node and edge in Cytoscape has an identifying name, most commonly used with the node
and edge data attribute structures. Node names must be unique as identically names nodes will
be treated as identical nodes. The name of each node will be the name in this file by default
(unless another string is mapped to display on the node using the visual mapper – see 9. Visual
Styles). The name of each edge will be formed from the name of the source and target nodes plus
the interaction type: for example, sourceName edgeType targetName.
The tag <interaction type> should be one of:
pp .................. protein – protein interaction
pd .................. protein -> DNA
(e.g. transcription factor binding upstream of a regulating gene.)
Any text string will work, but the above are the conventions that have been followed thus far.
Additional interaction types are also possible, but not widely used, e.g.:
pr .................. protein -> reaction
rc .................. reaction -> compound
cr .................. compound -> reaction
gl .................. genetic lethal relationship
pm .................. protein-metabolite interaction
mp .................. metabolite-protein interaction
Even whole words or concatenated words may be used to define other types of relationships e.g.
geneFusion, cogInference, pullsDown, activates, degrades, inactivates, inhibits,
phosphorylates, upRegulates
Delimiters. Whitespace (space or tab) is used to delimit the names in the simple interactions file
format. However, in some cases spaces are desired in a node name or edge type. The standard is
that, if the file contains any tab characters, then tabs are used to delimit the fields and spaces are
considered part of the name. If the file contains no tabs, then any spaces are delimiters that
separate names (and names cannot contain spaces).
If your network unexpectedly contains no edges and node names that look like edge names, it
probably means your file contains a stray tab that's fooling the parser. On the other hand, if your
network has nodes whose names are half of a full name, then you probably meant to use tabs to
separate node names with spaces.
Networks in simple interactions format are often stored in files with a ".sif" extension, and
Cytoscape recognizes this extension when browsing a directory for files of this type.
GML FORMAT:
In contrast to SIF, GML is a rich graph format language supported by many other network
visualization packages. The GML file format specification is available at:
http://www.infosun.fmi.uni-passau.de/Graphlet/GML/
It is generally not necessary to modify the content of a GML file directly. Once a network is
built in SIF format and then laid out, the layout is preserved by saving to and loading from GML.
Colors and other visual attribute defined in the GML file are not currently honored by Cytoscape,
only the node labels and layout information.
COMMANDS:
Load and save network files using the File menu of Cytoscape. Network files may also be loaded
directly from the command line using the –i (SIF format) or -g (GML format) options.
FOR EXAMPLE:
To load a sample molecular interaction network in
SIF format, use the menu File / Load / Graph. In
the resulting file dialog box, select the file
“sampleData/galFiltered.sif”. After a few seconds, a
small network of 331 nodes should appear in the main window. To load the same interaction
network as a GML, use the menu: File / Load / Graph again. In the resulting file dialog box,
select the file “sampleData/galFiltered.gml”. Node and edge attribute files as well as expression
data and extra annotation can be loaded as well.
NODE NAMING ISSUES IN CYTOSCAPE:
Typically, genes are represented by nodes, and interactions (or other biological relationships) are
represented by edges between nodes. For compactness, a gene also represents its corresponding
protein. Nodes may also be used to represent compounds and reactions (or anything else) instead
of genes.
If a network of genes or proteins is to be integrated with Gene Ontology (GO) annotation or gene
expression data, the gene names must exactly match the systematic ORF names specified in the
other data files. We strongly encourage naming genes and proteins by their systematic ORF
name or standard accession number; common names may be displayed on the screen for ease of
interpretation, so long as these are available to the program in the annotation directory or in a
node attribute file. Cytoscape ships with all yeast ORF-to-common name mappings in a synonym
table within the annotation/ directory. Other organisms will be supported in the future.
Why do we recommend using standard gene names? All of the external data formats recognized
by Cytoscape provide data associated with particular names of particular objects. For example, a
network of protein-protein interactions would list the names of the proteins, and the attribute and
expression data would likewise be indexed by the name of the object.
The problem is in connecting data from different data sources that don't necessarily use the same
name for the same object. For example, genes are commonly referred to by different names,
including a formal "location on the chromosome" identifier and one or more common names that
are used by ordinary researchers when talking about that gene. Additionally, database identifiers
from every database where the gene is stored may be used to refer to a gene (e.g. protein
accession numbers from Swiss-Prot). If one data source uses the formal name while a different
data source used a common name or identifier, then Cytoscape must figure out that these two
different names really refer to the same biological entity.
Cytoscape has two strategies for dealing with this naming issue, one simple and one more
complex. The simple strategy is to simply assume that every data source uses the same set of
names for every object. If this is the case, then Cytoscape can easily connect all of the different
data sources.
To handle data sources with different sets of names, as is usually the case when manually
integrating gene information from different sources, Cytoscape needs a data server that provides
synonym information (See section Appendix: Annotation Server Format). A synonym table gives
a canonical name for each object in a given organism and one or more recognized synonyms for
that object. Note that the synonym table itself defines what set of names are the "canonical"
names. For example, in budding yeast the ORF names are commonly used as the canonical
names.
If a synonym server is available, then by default Cytoscape will convert every name that appears
in a data file to the associated canonical name. Unrecognized names will be preserved. This
conversion of names to a common set allows Cytoscape to connect the genes present in different
data sources, even if they have different names – as long as those names are recognized by the
synonym server.
For this to work, Cytoscape must also be provided with the species to which the objects belong,
since the data server requires the species in order to uniquely identify the object referred to by a
particular name. This is usually done in Cytoscape by specifying the species name on the
command line with the –s option or by adding a line to the cytoscape.props file of the form:
defaultSpeciesName=Saccharomyces cerevisiae
The automatic canonicalization of names can be turned off with the -c command line argument
(i.e. java -jar cytoscape.jar -c) or by not loading any annotation. This canonicalization of names
currently does not apply to expression data. Expression data should use the same names as the
other data sources or use the canonical names as defined by the synonym table.
6. Loading Gene Expression Data
Interaction networks are certainly useful as stand-alone models. However, they are most
powerful for answering scientific questions when integrated with further information about the
biology associated with the network, such as gene or protein expression levels. Once loaded,
expression ratios/levels may be visually superimposed on the network, used in a filter to select a
subset of nodes, or used to identify active modules and subsystems (via plugin analysis tools).
An expression data set can be loaded at any time, but are only relevant once a network has been
loaded.
FORMAT:
Gene expression ratios are specified over one or more experiments using a text file. The file
consists of a header and a number of space- or tab-delimited fields, one line per gene, with the
following format:
GeneName [CommonName] ratio1 ratio2 ... ratioN [pval1 pval2 ... pvalN]
Brackets [] indicate fields that are optional. The first two fields are the systematic gene name
followed by an optional common name. Expression ratios are provided for each experiment,
optionally followed by a p-value per experiment or other measure of the significance of each
ratio, i.e. whether the ratio represents a true change in expression (according to some statistical
model.) Significance values are generated by a variety of software packages for analyzing
expression data generated by DNA microarrays, for instance a program VERA from the Institute
of Systems Biology (http://www.systemsbiology.org/VERAandSAM). A list of other microarray
analysis packages is available at: http://www.nslij-genetics.org/microarray/soft.html
Example:
GENE DESCRIPT gal1RG.sig gal2RG.sig gal3RG.sig gal1RG.sig gal2RG.sig gal3RG.sig
YHR051W
COX6 -0.034 -0.052 0.152 1.177 0.102 0.857
YHR124W
NDT80 -0.090 -0.000 0.041 0.130 0.341 0.061
YKL181W
PRS1 -0.167 -0.063 -0.230 -0.233 0.143 0.089
The first line is a header line giving the names of the experimental conditions. Note that each
condition is duplicated; the first set of columns gives expression ratios and the second set gives
significance values. The significance columns can be omitted if your data doesn't include
significance measures. Every remaining row specifies the values for a gene, starting with the
formal name of the gene, then a common name, then the ratios, then the significance values.
Some variations on this basic format are recognized: see the formal file format specification
below for more information. Expression data files commonly have the file extensions ".mrna" or
".pvals", and these file extensions are recognized by Cytoscape when browsing for data files.
COMMANDS:
Load an expression data file using the File menu of Cytoscape, or by specifying the filename
using the -e option at the command line. Mac OS X users, who have downloaded the Mac OS X
version of Cytoscape, can also drag SIF and GML file to the Cytoscape application to load those
files. The –x command line option indicates that the expression data should not be loaded into
node attributes. This is an advanced option, and is typically only used when the number of
expression conditions is sufficiently large that it becomes unwieldy in the normal user interface.
FOR EXAMPLE:
Load a sample gene expression data set using the menu: File / Load / Expression Matrix File. In
the resulting file dialog box (shown at right), select the file “sampleData/galExpData.pvals”. As
described in the following sections, Cytoscape is now ready to integrate these data with the
underlying molecular interaction network. Advanced Note: the checkbox in the lower left
corner of the file dialog asks whether to “Copy Expression Data to Graph Attributes” – unchecking this box has the same effect is as the command line option -x, and it is left checked by
default. If checked, this means that expression data values will be stored internally in Cytoscape
in two places, once in an internal expression data object and once in node attributes. The
advantage of also storing this information on node attributes is that the expression information
can be easily visualized.
Detailed file format (Advanced users)
In all expression data files, any whitespace (spaces and/or tabs) is considered a delimiter between
adjacent fields. Every line of text is either the header line or contains all the measurements for a
particular gene. No name conversion is applied to expression data files (see the section on name
resolution in section
5. Building and Storing Interaction Networks). The names given in the first column of the
expression data file should match exactly the names used elsewhere (i.e. in SIF or GML files).
The first line is a header line with one of the following three formats:
<text> <text> cond1 cond2 ... cond1 cond2 ... [NumSigConds]
<text> <text> cond1 cond2 ...
<tab><tab>RATIOS<tab><tab>...LAMBDAS
The first format specifies that both expression ratios and significance values are included in the
file. The first two text tokens are ignored; these columns will contain names for each gene. The
next token set specifies the names of the experimental conditions; these columns will contain
ratio values. This list of condition names must then be duplicated exactly, each spelled the same
way and in the same order. Optionally, a final column with the title NumSigConds may be
present. If present, this column will contain integer values indicating the number of conditions in
which each gene had a statistically significant change according to some threshold.
The second format is similar to the first except that the duplicate column names are omitted, and
there is no NumSigConds fields. This format specifies data with ratios but no significance values.
The third format specifies an MTX header, which is a commonly used format. Two tab
characters precede the RATIOS token. This token is followed by a number of tabs equal to the
number of conditions, followed by the LAMBDAS token. This format specifies both ratios and
significance values.
Each line after the first is a data line with the following format:
FormalGeneName CommonGeneName ratio1 ratio2 ... [lambda1 lambda2 ...] [numSigConds]
The first two tokens are gene names. The names in the first column are the keys used for node
name lookup; these names should be the same as the names used elsewhere in Cytoscape (i.e. in
the SIF or GML files). Traditionally in the gene expression microarray community, who defined
these file formats, the first token is expected to be the formal name of the gene (in systems where
there is a formal naming scheme for genes), while the second is expected to be a synonym for the
gene commonly used by biologists, although Cytoscape does not make use of the common name
column. The next columns contain floating point values for the ratios, followed by columns with
the significance values if specified by the header line. The final column, if specified by the
header line, should contain an integer giving the number of significant conditions for that gene.
Missing values are not allowed and will confuse the parser. For example, using two consecutive
tabs to indicate a missing value will not work; the parser will regard both tabs as a single
delimiter and be unable to parse the line correctly.
Optionally, the last line of the file may be a special footer line with the following format:
NumSigGenes int1 int2 ...
This line specified the number of genes that were significantly differentially expressed in each
condition. The first text token must be spelled exactly as shown; the rest of the line should
contain one integer value for each experimental condition.
7. Node and Edge Attributes
Cytoscape allows the user to add arbitrary node and edge information to Cytoscape as node and
edge attributes. Attributes could be, for example, annotation data on a gene or confidence
values in a protein-protein interaction. These attributes can then be visualized in a custom userdefined way by setting up a mapping from data attributes to visual attributes (colors, shapes, etc.)
(see section 9. Visual Styles).
Node and edge attribute files are very simply formatted: A node attribute file begins with the
name of the attribute on the first line, and on each following line, has the name of the node,
followed by an equals sign, followed by the value of that attribute. Numbers and text strings are
the most common attribute types. All values for a given attribute must have the same type. For
example:
FunctionalCategory
YAL001C = metabolism
YAR002W = apoptosis
YBL007C = ribosome
An edge attribute file has much the same structure, except that the name of the edge is the source
node name, followed by the interaction type in parentheses, followed by the target node name.
Directionality counts, so switching the source and target will refer to a different (or perhaps nonexistent) edge. The following is an example edge attributes file:
InteractionStrength
YAL001C (pp) YBR043W = 0.82
YMR022W (pd) YDL112C = 0.441
YDL112C (pd) YMR022W = 0.9013
Cytoscape treats edge attributes as directional, so note that the second and third edge attribute
values refer to two different edges (source and target are reversed, though the nodes involved are
the same).
Each attribute is stored in a separate file. Node and edge attribute files use the same format.
Node attribute file names often use the suffix ".noa", while edge attribute file names use the
suffix ".eda". Cytoscape recognizes these suffixes when browsing for attribute files.
Node and edge attributes may be loaded at the command line using the –n and –j options or via
the File / Load menu.
When expression data is loaded using an expression matrix file (See 6. Loading Gene Expression
Data), it is automatically copied into the Node Attributes data structure unless explicitly
specified not to.
Detailed file format (Advanced users)
Every attribute file has one header line that gives the name of the attribute, and optionally some
additional meta-information about that attribute. The format is as follows:
attributeName class=formal.class.of.value category=attributeCategory
The first field is always the attribute name: it cannot contain spaces. The file may optionally
include either of the class and category fields.
The category, if present, is saved and can be used by Cytoscape tools and plugins to group or
filter the set of available attributes.
If present, the class field defines the formal (package qualified) name of the class of the attribute
values. For example, java.lang.String for Strings, java.lang.Double for floating point
values, java.lang.Integer for integer values, etc. If the value is actually a list of values, the
class should be the type of the objects in the list. The value class must implement the Serializable
interface (see the object serialization section of the Java tutorial), allowing the data to be saved in
an efficient binary form (this binary attribute format is not directly supported by Cytoscape). If
the class is not a basic String or Number class, it should have a String representation and a
constructor that takes a String argument, allowing Cytoscape to construct an instance from the
String representation in the file.
If no class is specified in the header line, Cytoscape will attempt to guess the type from the first
value. If the first value contains numbers in a floating point format, Cytoscape will assume
java.lang.Double; if the first value contains only numbers with no decimal point, Cytoscape
will assume java.lang.Integer; otherwise Cytoscape will assume java.lang.String. Note
that the first value can lead Cytoscape astray: for example,
floatingPointAttribute
firstName = 1
secondName = 2.5
In this case, the first value will make Cytoscape think the values should be integers, when in fact
they should be floating point numbers. It's safest to explicitly specify the value type to prevent
confusion.
Every line past the first line identifies the name of an object and the String representation of the
attribute value. The delimiter is always an equals sign; whitespace (spaces and/or tabs) before
and after the equals sign is ignored. This means that your names and values can contain
whitespace, but object names cannot contain an equals sign and no guarantees are made
concerning leading or trailing whitespace. Usually the object names should be the same as the
names in your graph file, unless name conversion is being used (see the section on name
resolution in section
5. Building and Storing Interaction Networks). Edge names are all of the form
sourceName (edgeType) targetName
Note that this format is different from the specification of interactions in the SIF file format. To
be explicit: in a SIF file, an interaction looks like
sourceName edgeType targetName
To set an attribute for the edge defined by this interaction, the matching line in a attributes file
should look like
sourceName (edgeType) targetName = value
(Yes, this is confusing; we're planning on fixing this in the next file format update for
Cytoscape).
To specify lists of values, use the following syntax:
listAttributeName class=java.lang.String
firstObjectName = (firstValue::secondValue::thirdValue)
secondObjectName = (onlyOneValue)
This defines an attribute which is a list of Strings. The first object has three strings, and thus
three elements in its list, while the second object has a list with only one member. In the case of a
list every attribute value should be specified as a list, and every member of the list should be of
the same class. Again, the class will be inferred if it is not specified in the header line. Lists are
not supported by the visual mapper, so can’t be mapped to visual attributes.
8. Navigation and Layout
BASIC FEATURES:
Use the zooming buttons located on the toolbar to zoom in / out of the interaction network shown
in the current network display. Zoom icons are detailed below:
From Left to Right:
• Zoom Out
• Zoom In
• Zoom Selected Region
• Zoom out to Display all of Current Network
You can also zoom in/out by holding down the right mouse button and moving the mouse to the
right (zoom in) or left (zoom out).
Use the left mouse button to select a node (hold down the Shift key to select more than one
node). Use the right mouse button to launch a context sensitive menu with additional
information about the node that was clicked on.
NETWORK LAYOUT:
To lay out your network using a Spring Embedded Layout, select Layout Æ Apply Spring
Embedded Layout from the main menu. Sample screenshot is provided below:
Figure: Applying the Spring Embedded Layout to a sample network.
9. Visual Styles
With the Cytoscape Visual Style feature, you can easily customize the visual appearance of your
network. For example, you can specify a default color and shape for all nodes, use specific line
types to indicate different types of interactions, or visualize gene expression data using a color
gradient. All these features are available by selecting Visualization Æ Set Visual Properties
from the main menu or clicking on the color wheel in the main button bar menu.
9.1 Introduction to Visual Styles
The Cytoscape distribution you have downloaded includes three predefined visual styles to get
you started. To demonstrate these styles, try out the following example:
•
Load a sample network: From the main menu, select File Æ Load Æ Graph, and select
sampleData/galFiltered.sif.
•
Load a sample set of expression data: From the main menu, select File Æ Load Æ
Expression Matrix File, and select sampleData/galExpData.pvals.
By default, the Visual Style labeled “default” will be automatically applied to your network.
This default style has a blue background, circular pink nodes, and blue edges (see sample
screenshot below).
Visual Style
Pull-Down Menu
Figure: Using the default Visual Style.
The vizmap.props File: All Cytoscape Visual Style settings are automatically stored in a file
called vizmap.props. Upon startup, Cytoscape will first try to locate the vizmap.props file in
the “user home” directory. For example, on Windows XP, this corresponds to the user
“Documents and Settings” directory, e.g. c:\Documents and Settings\cerami. On Linux or Mac
OS X, this corresponds to the user home directory, e.g. /Users/cerami or ~. If no vizmap.props
file is found in the user’s home directory, Cytoscape will next search the current local
directory. Note: vizmap.props is a text file that can be edited, but it is not recommended. If
you do edit this file, make sure it is saved in text format and not that of any other editor.
[!] If you are upgrading from Cytoscape 1.1:
If you are upgrading from Cytoscape 1.1,
you may have an existing vizmap.props file in your home directory. If this is the case, you
will not have the sample1 and sample2 visual styles described below. To get around this issue,
backup your current vizmap.props file to safe place, and copy the new Cytoscape 2.1
vizmap.props file to your home directory.
You can flip through different visual styles by making a selection from the Visual Style pull
down menu. For example, if you select “Sample1”, a new visual style will be applied to your
network, and you will see a green background and round blue nodes. Additionally, protein-DNA
interactions (specified with the label: pd) are drawn with dashed edges, whereas protein-protein
interactions (specified with the label: pp) are drawn with drawn with a light yellow color which
is difficult to discern on the green background (see sample screenshot below). The background
can be changed through the Visualization menu.
Visual Style
Pull-Down Menu
Figure: Using the Sample1 Visual Style. Protein-Protein interactions (solid lines) are now distinguishable from Protein-DNA
interactions (dashed lines).
Finally, if you select “Sample2”, gene expression values for each node will be colored along a
color gradient between red and green (where red represents a low expression ratio, and green
represents a high expression ratio - with thresholds set for the gal1RGexp experiment bundled
with Cytoscape in the sampleData/galExpData.pvals file). See sample screenshot below:
Visual Style
Pull-Down Menu
Figure: Using the Sample2 Visual Style. Gene expression values are now displayed along a red/green color gradient.
9.2 Visual Attributes, Graph Attributes and Visual Mappers
The Cytoscape Visual Mapper has three core components: visual attributes, graph attributes and
visual mappers:
•
A visual attribute is any visual setting that can be applied to your network. For example,
you can change all nodes to squares by setting the node shape visual attribute.
•
A graph attribute is any attribute associated with a node or an edge. For example, each
edge in a network may be associated with a label, such as “pd” (protein-DNA
interactions), or “pp” (protein-protein interactions).
•
A visual mapper maps graph attributes to visual attributes. For example, a visual mapper
can map all protein-DNA interactions to the color blue, and all protein-protein
interactions to the color red.
Cytoscape includes a large number of visual attributes. These are summarized in the tables
below.
Visual Attributes Associated with Nodes:
•
Node Color
•
Node Border Color
•
Node Border Type. The following options are available:
•
Node Shape. The following options are available:
•
Node Size: width and height of each node.
•
Node Label: the text label for each node.
•
Node Font: node font and size.
Visual Attributes Associated with Edges:
•
Edge Color
•
Edge Line Type. The following options are available:
•
Edge Source Arrow. The following options are available:
•
Edge Target Arrow. The following options are available:
•
Edge Label: the text label for each edge.
•
Edge Font: edge font and size.
Global Visual Properties:
•
Background Color
For each visual attribute, you can specify a default value or define a visual mapping. Cytoscape
currently supports three different types of visual mappers:
•
Passthrough Mapper: graph attributes are passed directly through to visual attributes.
A passthrough mapper only works for node / edge labels. For example, a passthrough
mapper can draw the common gene name on all nodes.
•
Discrete Mapper: discrete graph attributes are mapped to discrete visual attributes. For
example, a discrete mapper can map all protein-protein interactions to the color blue.
•
Continuous Mapper: continuous graph attributes are mapped to visual attributes.
Depending on the visual attribute, there are two types of continuous mappers:
o continuous to continuous mapper: for example, you can map a continuous
value (0..1) to a color gradient (red..green) or node/font size (10..100).
o continuous to discrete mapper: for example, all values below 0 are mapped to
square nodes, and all values above 0 are mapped to circular nodes. However,
there is no way to smoothly morph between circular nodes and square nodes.
The matrix below shows visual mapper support for each visual property.
Passthrough
Mapper
Discrete
Mapper
Continuous
Mapper
Node Properties
Node Color
Node Border Color
Node Border Type
Node Shape
Node Size
Node Label
Node Font Family
Node Font Size
Edge Properties
Edge Color
Edge Line Type
Edge Source Arrow
Edge Target Arrow
Edge Label
Edge Font Family
Edge Font Size
[
[
[
[
[
●
[
[
●
●
●
●
●
●
●
●
●
●
◗
◗
●
◗
◗
●
[
[
[
[
●
[
[
●
●
●
●
●
●
●
●
◗
◗
◗
◗
◗
●
Legend
[
Mapping is not supported for specified visual property.
●
Mapping is fully supported for specified visual property.
◗
Mapping is partially supported for specified visual property. Support for
“continuous to continuous” mapping is not supported.
9.3 Tutorial: Creating a New Visual Style
To create a new visual style, select Visualization Æ
Set Visual Properties from the main menu, or select
the color wheel icon in the main button bar. You will
now see a new Visual Styles dialog box (shown at
right.)
Visual Property Categories
Click the New button, and enter a name for your new visual style
when prompted. Then click the Define button. You will now
see the main Visual Styles Properties dialog box (shown at right.)
From this dialog box, you can flip between Node Attributes,
Edge Attributes, and Global Defaults. You can also specify
default values for any visual property, or define a new custom
mapping.
Create a new mapper.
For example, to set the default node shape to triangles, select
Node Attributes Æ Node Shape. Then, click the “Change
Default” button, and select the Triangle icon from the selection
list.
Applying Changes to the Network
To apply your visual style to your network, hit the “Apply to Graph”
button, available in the bottom of the dialog panel.
Select the Apply button to apply
your newly revised style to the
graph.
Saving a Visual Style
When you exit Cytoscape, new visual styles or newly modified visual styles will automatically
be saved in the vizmap.props file. You can therefore create a new visual style and apply it to all
future networks.
9.4 Tutorial: Creating a New Visual Style with a Discrete
Mapper
The following tutorial demonstrates how to create a new visual
style with a discrete mapper. The goal is to draw Protein-DNA
interactions with blue edges, and Protein-Protein interactions with
red edges.
•
•
•
•
•
•
•
•
•
•
•
Load a sample network: From the main menu, select File
Æ Load Æ Graph, and select sampleData/galFiltered.sif.
Select Visualization Æ Set Visual Properties.
Select “New” to create a new Visual Style. Name your
new style: “Sample3”.
Click the “Define” button to define the newly created
Visual Style.
In the “Set Visual Properties” Dialog box, select Edge
Attributes Æ Edge Color.
Click the New button in the mapping panel.
You will be prompted to select a mapping type:
passthrough mapper, discrete mapper or continuous mapper (for an overview of the
differences between these mappers, please refer back to section 8.2.) Select “discrete
mapper”, and enter a descriptive name. For example, enter: “InteractionTypeColor”.
From the “Map Attribute” pull-down menu, select “interaction.” You should now see
two buttons, one for pd (Protein-DNA interactions), and one for pp (Protein-Protein
interactions).
Click the “pd” button and select a blue
color.
Click the “pp” button and select a red
color.
Click the “Apply to Graph” button.
You network should now show “pd” interactions
in blue, and “pp” interactions in red. Sample
screenshot is provided at right
9.5 Tutorial: Visualizing Expression Data on a Network
The following tutorial demonstrates how to create a new continuous mapper. The goal is to
superpose gene expression data onto a network, and to display gene expression values along a
color gradient.
•
•
•
•
•
•
•
•
•
•
•
•
•
Load a sample network: From the main menu,
select File Æ Load Æ Graph, and select
sampleData/galFiltered.sif.
Load a sample set of expression data: From the
main menu, select File Æ Load Æ Expression
Matrix File, and select
sampleData/galExpData.pvals.
Select Visualization Æ Set Visual Properties.
Select “New” to create a new Visual Style. Name
your new style: “Sample4”.
Click the “Define” button to define the newly
created Visual Style.
In the “Set Visual Properties” Dialog box, select
Node Attributes Æ Node Color.
Click the New button in the mapping panel.
You will be prompted to select a mapping type:
passthrough mapper, discrete mapper or
continuous mapper (for an overview of the
differences between these mappers, please refer back to section 8.2.) Select “continuous
mapper”, and enter a descriptive name. For example, enter: “ColorGradient”.
From the “Map Attribute” pull-down menu, select “gal1RGexp.”
Click the “Add Point” button twice to add two data points.
Set the first point to “-1”, Below = Yellow, Equal = White.
Set the second point to “2”, Equal = Red, Above = Black.
Click the “Apply to Graph” button.
This visual mapper will set all nodes with a
gal1RGexp value less than –1 to Yellow, and
all nodes with a gal1RGExp value greater than
2 to Black. Additionally, all values between –
1 and 2 will be painted with a white/red color
gradient. Sample screenshot is shown at right.
10. Filters
The Cytoscape Filter plugin, which is packaged with the official Cytoscape 2.1 release
and is active by default, allows for a wide variety of fine-tuned filtering on node and edge
attributes loaded onto Cytoscape networks. For example, you can easily select all the nodes
whose name contains a specific pattern that you define. Example filters are shipped with the
plugin to get started. Base filters only operate on String and Scalar data i.e. any names,
descriptions or numerical node or edge attributes can be filtered. A Boolean filter is also
available that can be used to combine any number of existing filters in logical combinations, so
as you add filters, the plugin becomes more powerful.
Using the Plugin
If the Filter plugin is loaded, then you should see a menu called “Filters” and the filter
icon:
Activate the filters using either the “Use Filters” menu entry or the large filters icon (red
and green arrows). The filters dialog looks like the following (without the colors...)
As for the colors:
The Red Box: Each available filter has its own tab. The default filter is Node Interactions
(which allows you to filter nodes, based on the edges that they are connected to), Boolean
(which allows you to combine filters together using AND, OR and XOR operators), Topology
(which allows you to filter nodes based on the number of edges to other nodes), Numerical
(which allows for >, =, and < filtering operations on numerical attributes) and String (which
allows for filtering using * and ? as wildcards).
The Purple Box: An existing or newly created filter can be edited in this area. Each filter type
has its own user interface for editing.
The Orange Box: All available filters are shown in this list. Initially, this list will contain sample
filters, but as you create more, they will be added here.
The Cyan Box: Pressing “Add Current Filter” adds the filter being edited to the “Available
Filters” box, and “Remove Selected Filter” deletes the currently selected filter.
The Green Box: This area contains default actions for a given filter. These specify how
Cytoscape should display the network components (nodes and edges) that pass a filter. You can
choose to have Cytoscape select the nodes and/or edges that pass a given filter or alternatively
have Cytoscape hide the nodes and/or edges that do not pass a given filter. A useful operation is
to have a filter select a set of nodes and then send these nodes to a new network (through the
Select menu).
Creating Filters
The important thing to realize when creating a filter is that the filter does not do anything
by itself. Once created, the filter must be run.
String Filter:
The String Filter allows you to choose to Filter Node or Edges, and gives you a list of available
attributes to search for each (those attributes that are loaded on the network). If you have the
filters dialog box active and you load new graph attributes, you can click the update button to
refresh the attribute list. Search terms are entered in the text box at the bottom. For example to
match any Node whose canonicalName starts with “YDL” you would select “Node”,
“canonicalName” and type “YDL*”. The * is important as it matches anything for any number of
characters after YDL. If you want to be more specific and only select Nodes whose
canonicalName starts with YDL00 followed by any other two characters, you would type
“YDL00??”. The “?” denotes any single character, while the “*” represents zero or more
characters. Full regular expression searching is supported, although is not covered here. Once the
filter is defined, it will be assigned a default descriptive name, although this name can be edited.
Pressing the “Add Current Filter” button will add your filter to the list of available filters to the
left.
Numerical Filter:
The Numerical Filter also allows you to filter Nodes or Edges, and presents you with a list of
available attributes. This filter matches greater-than, less-than, or equal-to a number you type in
the search box. See the String filter description for more information.
Boolean Filter:
The Boolean filter allows you to define a new filter that is a logical combination of existing
filters. Available filters are displayed (although the list can be refreshed by clicking the “Update
List of Filters” button). By selecting one or more filters, you can then choose whether Nodes or
Edges pass “ALL” (AND), “AT LEAST ONE” (OR), or “ONLY ONE” (XOR) of the selected
filters. Once created Boolean filters can then themselves be combined using the Boolean filter to
create arbitrarily complex logical combinations of filters. Note that unlike the String and
Numerical Filters, Boolean Filters will need to be assigned a name manually.
Once created, filters are saved for future sessions, as long as you exit Cytoscape normally via the
exit command in the File menu (i.e. not via ctrl-c on Linux).
Running filters
Any available filter can be run by selecting a visualization action for Cytoscape (how your filter
results should be displayed) and pressing the ‘Go!’ button.
The Network +/- Filter Feature
The “Network +/-” dialog is available from the Filters menu. It allows you to create new
networks and add/remove nodes to/from existing networks based on available filters. The dialog
box is shown below:
The Attribute Browser Filter Feature
The “Attributes Browser if passed Filter” item from the Data menu allows you to see the normal
Cytoscape graph attribute browser for all nodes or edges that pass a given filter.
Once clicked, the following dialog box appears to allow you to choose an available filter:
Clicking on the Browser button will open the graph attributes browser.
The Diff Filter Feature
The Diff feature, accessible from the Data menu shown above, allows you to see which nodes or
edges pass each of two selected filters and which nodes or edges those filters don’t have in
common (i.e. it shows the differences between two filters). This is useful for quickly comparing
two filters. You can then create a new network that contains the differences (“Create Network”
button) or create a new filter that selects the differences (“Create Filter” button).
The same functionality is available here for networks. You can select any two networks that are
loaded and create a new network from their differences.
11. Acknowledgements
Cytoscape is built with a number of open source 3rd party Java libraries. The Cytoscape team
gratefully acknowledges the following libraries:
•
The Colt Distribution: Open Source Libraries for High Performance Scientific and
Technical Computing in Java. Information is available at:
http://hoschek.home.cern.ch/hoschek/colt/.
•
GNU Getopt in Java. Information is available at:
http://www.urbanophile.com/arenn/hacking/download.html.
•
Graph INterface librarY a.k.a. GINY. Information is available at:
http://csbi.sourceforge.net/.
•
JDOM. Information is available at: http://www.jdom.org.
•
JUnit. Information is available at: http://junit.org.
•
JGoodies Looks. Information is available at:
http://www.jgoodies.com/freeware/looks/index.html.
•
Piccolo. Information is available at: http://www.cs.umd.edu/hcil/jazz/.
•
Type-Specific Collections Library, from Sosnoski Software Solutions, Inc. Information
is available at: http://www.sosnoski.com/opensrc/tclib/.
•
Xerces Java XML parser. Information is available at: http://xml.apache.org/xerces-j/.
This product includes software developed by the Apache Software Foundation
(http://www.apache.org/).
This product includes software developed by the JDOM Project (http://www.jdom.org/).
Appendix: Annotation Server Format
This section for advanced users.
Introduction
Annotation in Cytoscape is stored as a set of ontologies (e.g. the Gene Ontology), a set of
ontology controlled vocabulary term annotations for the genes from a given organism and a
synonym table for gene names. For example, using the Gene Ontology, the Saccharomyces
Cerevisiae GAL4 gene’s biological process is described as “regulation of transcription”, to
which GO has assigned the number 45449 (a GO ID). You can see below that “regulation of
transcription” is a subcategory of “transcription”, which is a subcategory of “nucleobase,
nucleoside, nucleotide and nucleic acid metabolism”, etc.
GO 8150 biological_process
GO 7582 physiological processes
GO 8152 metabolism
GO 6139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism
GO 6350 transcription
GO 45449 regulation of transcription
Cytoscape can use this ‘hierarchical’ ontology to annotate recognized genes, provided the user
chooses a level of the hierarchy to use for a given set of annotations. The ontology provided to
Cytoscape does not have to be hierarchical, but if it is not, there is no real advantage to storing
annotations this way compared to just storing the annotation terms in a node attribute file.
The annotation server (originally called the biodata server) is a Cytoscape feature which allows
you to load, navigate, and assign annotation terms to nodes in a network.
There are two modes in which an annotation server can be run:
1. As an in-process version of the same code, that runs in the same Java Virtual Machine as
Cytoscape. This is the default for the official release of Cytoscape.
2. As a separately running program, an RMI server with which Cytoscape communicates.
The RMI server is especially useful if there are multiple Cytoscape users all running in the same
location, using the same annotation: a group of yeast biologists, for example, all within the same
institute or if a group studies several organisms (yeast, human, mouse ...). The RMI server is a
little bit of trouble to set up, however, and so many people will elect to use the in-process server.
Building your own annotation files
The annotation server requires that the gene annotations, and associated ontology on controlled
vocabulary terms, follow a simple format. This simple format was chosen because it is efficient
to parse and easy to use.
The flat file formats are explained below:
The Ontology Format
By example (the Gene Ontology - GO):
(curator=GO) (type=all)
0003673 = Gene_Ontology
0003674 = molecular_function [partof: 0003673 ]
0008435 = anticoagulant [isa: 0003674 ]
0016172 = antifreeze [isa: 0003674 ]
0016173 = ice nucleation inhibitor [isa: 0016172 ]
0016209 = antioxidant [isa: 0003674 ]
0045174 = glutathione dehydrogenase (ascorbate) [isa: 0009491 0015038 0016209 0016672 ]
0004362 = glutathione reductase (NADPH) [isa: 0015038 0015933 0016209 0016654 ]
0017019 = myosin phosphatase catalyst [partof: 0017018 ]
...
A second example (KEGG pathway ontology):
(curator=KEGG) (type=Metabolic Pathways)
90001 = Metabolism
80001 = Carbohydrate Metabolism [isa: 90001 ]
80003 = Lipid Metabolism [isa: 90001 ]
80002 = Energy Metabolism [isa: 90001 ]
80004 = Nucleotide Metabolism [isa: 90001 ]
80005 = Amino Acid Metabolism [isa: 90001 ]
80006 = Metabolism of Other Amino Acids [isa: 90001 ]
80007 = Metabolism of Complex Carbohydrates [isa: 90001 ]
...
The format has three required features:
1. The first line contains two parenthesized assignments, for curator and type. In the GO
example above, the ontology file (which is created from the XML GO provides) nests all
three specific ontologies (molecular function, biological process, cellular component)
below the 'root' ontology, named 'Gene_Ontology'.
(type=all)
tells you that all three ontologies are included in that file.
2. Following the mandatory title line, there are one or more category lines, each with the
form:
number0 = name [isa:|partof: number1 number2 ...]
'isa' and 'partof' are terms used in GO; they describe the relation between parent and child
terms in the ontology hierarchy.
3. The trailing blank before each left square bracket is not required; it is an artifact of the
python script that creates these files.
The Annotation Format
By example (from the GO biological process annotation file):
(species=Saccharomyces cerevisiae) (type=Biological Process) (curator=GO)
YMR056C = 0006854
YBR085W = 0006854
YJR155W = 0006081
...
and from KEGG:
(species=Mycobacterium tuberculosis) (type=Metabolic Pathways) (curator=KEGG)
RV0761C = 10
RV0761C = 71
RV0761C = 120
RV0761C = 350
RV0761C = 561
RV1862 = 10
...
The format has these required features:
1. The first line contains three parenthesized assignments, for species, type and curator. In
the example just above, the annotation file (which we create for budding yeast from the
flat text file maintained by SGD for the Gene Ontology project, and available both at
their web site and at GO's) shows three yeast ORFs annotated for biological process, with
respect to GO, described (further above).
2. Following the mandatory title line, there are one or more annoation lines, each with the
form:
canonicalName = ontologyTermID
3. Once loaded, this annotation (along with accompanying ontology) can be assigned to
nodes in a Cytoscape network. For this to work, the species type of the node must
agree exactly with the species named on the first line of the annotation file. The
canonicalName of your node must exactly match the canonicalName present in the
annotation file. If you don’t see the expected results when using this feature of
Cytoscape, check this again, as getting either of these wrong is a common mistake.
Load Data In-Process
The easiest way to make annotation available to Cytoscape is by loading annotation into an inprocess annotation server. This is the default for the official release of Cytoscape.
The Annotation Manifest
You must first create a text file to specify the files you want Cytoscape to load. Here is an
example, from a file which (for convenience) we usually call “manifest”
ontology=goOntology.txt
annotation=yeastBiologicalProcess.txt
annotation=yeastMolecularFunction.txt
annotation=yeastCellularComponent.txt
Use the Cytoscape -b command line argument to specify the annotation manifest file to read (e.g.
-b manifest). Please note that the -s switch, which sets the default species for your data is
required to exactly match the species named in any annotation file you wish to use.
Getting and Reformatting GO Data
The Gene Ontology (GO) project is a valuable source of annotation for the genes of many
organisms. In this section we will explain how to:
1.
2.
3.
4.
Obtain the GO ontology file
Reformat it into the simpler flat file Cytoscape uses
Obtain an annotation file (we illustrate with yeast and human annotation)
Reformat the annotation files into the simple Cytoscape format
Obtain the GO ontology file
Go to the GO XML FTP (ftp://ftp.geneontology.org/pub/go/xml/) page. Download the latest goYYYYMM-termdb.xml.gz file.
Reformat GO XML ontology file into a flat file
gunzip go-YYYYMM-termdb.xml.gz
python parseGoTermsToFlatFile.py
go-YYYYMM-termdb.xml > goOntology.txt
(See below for Python script listing)
Obtain the 'association' file for your organism
GO maintains a list of association files for many organisms; these files associate genes with GO
terms. The next step is to get the file for the organism/s you are interested in, and parse it into the
form
Cytoscape
needs.
A
list
of
files
may
be
seen
at
http://www.geneontology.org/GO.current.annotations.shtml. The rightmost column contains
links to tab-delimited files of gene associations, by species. Choose the species you are interested
in, and click 'Download'.
Let's use 'GO Annotations @ EBI Human' as an example. After you have downloaded and
saved the file, look at the first few lines:
SPTR
O00115 DRN2_HUMAN
Deoxyribonuclease II precursor
SPTR
O00115 DRN2_HUMAN
Deoxyribonuclease II precursor
SPTR
O00115 DRN2_HUMAN
Deoxyribonuclease II precursor
GO:0003677
IPI00010348
protein
GO:0004519
IPI00010348
protein
GO:0004531
IPI00010348
protein
PUBMED:9714827
taxon:9606
GOA:spkw
taxon:9606
PUBMED:9714827
taxon:9606
TAS
F
SPTR
IEA
20020425
TAS
SPTR
F
SPTR
F
...
Note that line wrapping has occurred here, so each line of the actual file is wrapped to two lines.
The goal is to create from these lines the following lines:
(species=Homo
IPI00010348 =
IPI00010348 =
IPI00010348 =
...
sapiens) (type=Molecular Function) (curator=GO)
0003677
0004519
0004531
or
(species=Homo sapiens) (type=Biological Process) (curator=GO)
NP_001366 = 0006259
NP_001366 = 0006915
NP_005289 = 0007186
NP_647593 = 0006899
...
The first sample contains molecular function annotation for proteins, and each protein is
identified by its IPI number. IPI is the International Protein Index, which maintains cross
references to the main databases for human, mouse and rat proteomes.
The second sample contains biological process annotation, and each protein is identified by its
NP (RefSeq) number.
These two naming systems, IPI and RefSeq, are two of many that you can use for canonical
names when you run Cytoscape. For budding yeast, it is much easier: the yeast community
always uses standard ORF names, and so Cytoscape uses these as canonical names. For human
proteins and genes, there is no such single simple standard. See section
5. Building and Storing Interaction Networks for more information.
The solution (for those working with human genes or proteins) is, once you have downloaded the
annotations file, to:
1. Decide which naming system you want to use.
2. Download ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/HUMAN/xrefs.goa. This crossreference file, when used strategically, allows you to create Cytoscape-compatible
annotation files in which the canonical name is the one most meaningful to you.
3. Examine xrefs.goa to figure out which column contains the names you wish to use.
4. Make a very slight modification to the python script described below, and then
5. Run that script, supplying both xrefs.goa and that annotation file as arguments.
Here are a few sample lines from xrefs.goa:
SP
SP
SP
...
O00115 IPI00010348
ENSP00000222219;
NP_001366;
BAA28623;AAC77366;AAC35751;AAC39852;BAB55598;AAB51172;AAH10419;
1777,DNASE2
O00116 IPI00010349
ENSP00000324567;ENSP00000264167;
CAA70591;
327,AGPS
8540,AGPS
O00124 IPI00010353
ENSP00000265616;ENSP00000322580;
BAA18958;BAA18959;AAH20694;
7993,D8S2298E
2960,DNASE2
NP_003650;
NP_005662;
Note that line wrapping has occurred here – each line in this example starts with the letters SP.
See the README file for more information
(ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/HUMAN/README)
Finally, run the script to create your three annotation files for human proteins:
•
•
•
bioproc.anno (GO biological process annotation)
molfunc.anno (GO molecular function annotation)
cellcomp.anno (GO cellular component annotation)
using the supplied python script. It may be necessary to modify this script slightly if RefSeq
identifiers are not used as canonical names.
python parseAssignmentsToFlatFileFromGoaProject.py gene_association.goa_human xrefs.goa
(See below for Python script listing)
Python script examples:
These scripts, described above require Python version 2.2 or later.
Script 1 - parseGoTermsToFlatFile.py
# parseGoTermToFlatFile.py: translate a GO XML ontology file into a simpler
# Cytoscape flat file
#----------------------------------------------------------------------------------# RCS: $Revision: 1.3 $
$Date: 2003/05/18 00:38:43 $
#----------------------------------------------------------------------------------import re, pre, sys
#----------------------------------------------------------------------------------def flatFilePrint (id, name, isaIDs, partofIDs):
isa = ''
if (len (isaIDs) > 0):
isa = '[isa: '
for isaID in isaIDs:
isa += isaID
isa += ' '
isa += ']'
partof = ''
if (len (partofIDs) > 0):
partof = '[partof: '
for partofID in partofIDs:
partof += partofID
partof += ' '
partof += ']'
result = '%s = %s %s %s' % (id, name, isa, partof)
result = result.strip ()
if (result == 'isa = isa' or result == 'partof = partof'):
print >> sys.stderr, 'meaningless term: %s' % result
else:
print result
#----------------------------------------------------------------------------------if (len (sys.argv) != 2):
print 'usage: %s <someFile.xml>' % sys.argv [0]
sys.exit ();
inputFilename = sys.argv [1];
print >> sys.stderr, 'reading %s...' % inputFilename
text = open (inputFilename).read ()
print >> sys.stderr, 'read %d characters' % len (text)
regex = '<go:term .*?>(.*?)</go:term>';
cregex = pre.compile (regex, re.DOTALL)
# . matches newlines
m = pre.findall (cregex, text)
print >> sys.stderr, 'number of go terms: %d' % len (m)
regex2 = '<go:accession>GO:(.*?)</go:accession>.*?<go:name>(.*?)</go:name>'
cregex2 = re.compile (regex2, re.DOTALL)
regex3 = '<go:isa\s*rdf:resource="http://www.geneontology.org/go#GO:(.*?)"\s*/>'
cregex3 = re.compile (regex3, re.DOTALL)
regex4 = '<go:part-of\s*rdf:resource="http://www.geneontology.org/go#GO:(.*?)"\s*/>'
cregex4 = re.compile (regex4, re.DOTALL)
goodElements = 0
badElements = 0
print '(curator=GO) (type=all)'
for term in m:
m2 = re.search (cregex2, term)
if (m2):
goodElements += 1;
id = m2.group (1)
name = m2.group (2)
isaIDs = []
m3 = re.findall (cregex3, term);
for ref in m3:
isaIDs.append (ref)
m4 = re.findall (cregex4, term);
partofIDs = []
for ref in m4:
partofIDs.append (ref)
flatFilePrint (id, name, isaIDs, partofIDs)
else:
badElements += 1;
print >> sys.stderr, 'no match to m2...'
print >> sys.stderr, "---------------\n%s\n------------------" % term
print >> sys.stderr, 'goodElements %d' % goodElements
print >> sys.stderr, 'badElements %d' % badElements
#--------------------------------------
Script 1 - parseAssignmentsToFlatFileFromGoaProject.py
#!/tools/bin/python
import sys
#----------------------------------------------------------------------------------def fixCanonicalName (rawName):
# for instance, trim 'YBR085W|ANC3' to 'YBR085W'
bar = rawName.find ('|')
if (bar < 0):
return rawName
return rawName [:bar]
#----------------------------------------------------------------------------------def fixGoID (rawID):
bar = rawID.find (':') + 1
return rawID [bar:]
#----------------------------------------------------------------------------------def readGoaXrefFile (filename):
lines = open (filename).read().split ('\n')
result = {}
for line in lines:
if (len (line) < 10):
continue
tokens = line.split ('\t')
ipi = tokens [2]
np = tokens [5]
semicolon = np.find (';')
if (semicolon >= 0):
np = np [:semicolon]
if (len (ipi) > 0 and len (np) > 0):
result [ipi] = np
return result
#----------------------------------------------------------------------------------if (len (sys.argv) != 3):
print 'error! parse
<gene_associations file from GO> <goa xrefs file> '
sys.exit ()
associationFilename = sys.argv [1];
xrefsFilename = sys.argv [2]
species = 'Homo sapiens'
ipiToNPHash = readGoaXrefFile (xrefsFilename)
tester = 'IPI00099416'
print 'hash size: %d' % len (ipiToNPHash)
print 'test map: %s -> NP_054861: %s ' % (tester, ipiToNPHash [tester])
bioproc = open ('bioproc.txt', 'w')
molfunc = open ('molfunc.txt', 'w')
cellcomp = open ('cellcomp.txt', 'w')
bioproc.write ('(species=%s) (type=Biological Process) (curator=GO)\n' % species)
molfunc.write ('(species=%s) (type=Molecular Function) (curator=GO)\n' % species);
cellcomp.write ('(species=%s) (type=Cellular Component) (curator=GO)\n' % species);
lines=open(associationFilename).read().split('\n')
sys.stderr.write ('found %d lines\n' % len (lines))
for line in lines:
if (line.find ('!') == 0 or len (line) < 2):
continue
tokens = line.split ('\t')
goOntology = tokens [8]
goIDraw = tokens [4]
goID = goIDraw.split (':')[1]
ipiName = fixCanonicalName (tokens [10])
if (len (ipiName) < 1):
continue
if (not ipiToNPHash.has_key (ipiName)):
continue
refseqName = ipiToNPHash [ipiName]
printName = refseqName
#printName = ipiName
if (ipiName == tester):
print '%s (%s) has go term %s' % (tester, printName, goID)
if (goOntology == 'C'):
cellcomp.write ('%s = %s\n' % (printName, goID))
elif (goOntology == 'P'):
bioproc.write ('%s = %s\n' % (printName, goID))
elif (goOntology == 'F'):
molfunc.write ('%s = %s\n' % (printName, goID))
#-----------------------------------------------------------------------------------
Appendix: GNU Lesser General Public License
GNU LESSER GENERAL PUBLIC LICENSE
Version 2.1, February 1999
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